<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Data mining is the progress of automatically discovering high level data and trends in large amounts of data that would otherwise remain hidden. In order to improve the privacy preservation of association rule mining, a hybrid partial hiding algorithm (HPH) is proposed. The original data set can be interfered and transformed by different random parameters. Then, the algorithm of generating frequent items based on HPH is presented. Finally, it can be proved that the privacy of HPH algorithm is better than that of the original algorithm.</p></abstract>

Data mining is the progress of automatically discovering high level data and trends in large amounts of data that would otherwise remain hidden. In order to improve the privacy preservation of association rule mining, a hybrid partial hiding algorithm (HPH) is proposed. The original data set can be interfered and transformed by different random parameters. Then, the algorithm of generating frequent items based on HPH is presented. Finally, it can be proved that the privacy of HPH algorithm is better than that of the original algorithm.

A New Privacy Preserving Association Rule Mining Algorithm Based on Hybrid Partial Hiding Strategy

School of Information, Central University of Finance and Economics, Beijing 100081, China

Cybernetics and Information Technologies

Data mining is the progress of automatically discovering high level data and trends in large amounts of data that would otherwise remain hidden. In order to...

A New Privacy Preserving Association Rule Mining Algorithm Based on Hybrid Partial Hiding Strategy

Online veröffentlicht: 31. Dez. 2013

Seitenbereich: 41 - 50

DOI: https://doi.org/10.2478/cait-2013-0036

This content is open access.